Panel on December 17, 2024 3:50 - 4:20 PM ET - Riki to attend
Looking for talking points for answers for these 3 questions that will be discussed on the panel:
Question 1: Please briefly refresh the audience regarding the vision, objectives, key participants, and scope of activities in your Collaborative Community, including highlights of recent and ongoing activities and upcoming milestones or events. [3-5 minutes]
SHIELD stands for Systemic Harmonization and Interoperability Enhancement for Laboratory Data (SHIELD)
We have over 70 organizations representing federal agencies, in vitro diagnostics (IVD) organizations, standards development organizations , medical associations, and other professional laboratory organizations
SHIELD’s mission is to “Describe the SAME test the SAME way ANYWHERE in the Healthcare ecosystem”
We work on interoperability issues because it allows accurate public health surveillance and response; provides confidence by patients and doctors in laboratory results; and ensures medical researchers that their studies can be reproduced.
Broken out in several Working Groups that tackle different parts of the SHIELD Roadmap:
Standardization and Vocabulary
alginment for specific lab test areas (e.g. how to best represent and report susceptibility testing (phenotypic and genotypic)
creation of common value sets for qualitative tests
Laboratory Interoperability Data Repository (LIDR)
creating a library of vendor specific lab test characteristics that also provides proper coding for all its data exchange elements (LOINC for the tests, SNOMED CT for coded result values, specimen information, methods), UCUM for units of quantitative result values)
Communication and Branding
getting the word out at conferences and in articles
outreach to SHIELD membership
IVD Data Hub
creating a home for de-identified test specific results for secondary use
post-market research
clinical research
public health
FDA BAA work with participation from SHIELD members:
Question 2: What have been the biggest challenges or barriers to achieving standardized methodology and data structures (interoperability) across variety of data-generating devices, lab tests, and organizations?
Limited resources allocated for this work - by clinicians, HIT vendors, federal agencies results in limited time commitment for human resources and no available funding for pilot projects
inconsistent definitions for clinical data can result in similar, but not identical data structures or vocabulary, which results in potential loss of information during transformation or if the difference is not identified mismatches altogether
Question 3 [back-up, time-permitting]: How has your CC sought to balance the competing needs for both innovation & standardization?
unsure if these two things actually interfere with each other, except maybe that getting true consensus across a large healthcare ecosystem takes time, while innovation often works in quicker sprints - trying to break down consensus building into smaller projects could mitigate some of that
test
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